Готові списки джерел за темами / INTEGRATING TEXT

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Добірка наукової літератури з теми "INTEGRATING TEXT"

Автор: Grafiati
Опубліковано: 11 вересня 2023

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Статті в журналах з теми "INTEGRATING TEXT"

1

Nazari, Narges Honarvar, Tianxiang Tan, and Yao-Yi Chiang. "Integrating Text Recognition for Overlapping Text Detection in Maps." Electronic Imaging 2016, no. 17 (February 17, 2016): 1–8. http://dx.doi.org/10.2352/issn.2470-1173.2016.17.drr-061.

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2

Frantz, Paul, and Caleb Tucker‐Raymond. "Integrating text messaging into reference services." Library Hi Tech News 28, no. 5 (July 5, 2011): 8–9. http://dx.doi.org/10.1108/07419051111163839.

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3

Raudhotul Muthoharoh, Nada, Nurhaedah Gailea, and Syafrizal Syafrizal. "Integrating Blended Learning and Peer Feedback in Teaching Writing Recount Text and Vocabulary." Journal of English Language Teaching and Cultural Studies 5, no. 1 (March 28, 2022): 34–41. http://dx.doi.org/10.48181/jelts.v5i1.14656.

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Анотація:
This research aims to investigate the integration of blended learning and peer feedback technique in teaching writing recount text and vocabulary mastery. The research applied quasi-experimental design. The population of this study was second grade of MTs Daarul Muqimien and 60 students as the samples. The data collection techniques used the test of writing skill and vocabulary mastery and the data of this research was analyze by using statistics Manova (Multivariate Analysis of Variants) with the helped of SPSS Statistics 22 Software. The result shows the significant value of students writing recount text by integrating blended learning and peer feedback technique is 0.000<0.05 F count 28.095, the significant value of students’ vocabulary mastery by integrating blended learning and peer feedback technique is 0.009<0.05 F count 7.203, and significant value of students writing recount text and vocabulary mastery by integrating blended learning and peer feedback technique is 0.000<0.05, F count 13.884. Based on the result, it concludes that there is a significant influence of students’ writing recount text and vocabulary mastery group through integrating blended learning and peer feedback technique.
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4

Appelt, Wolfgang. "Existing systems for integrating text and graphics." Computers & Graphics 11, no. 4 (January 1987): 369–75. http://dx.doi.org/10.1016/0097-8493(87)90053-7.

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Shatkay, H., N. Chen, and D. Blostein. "Integrating image data into biomedical text categorization." Bioinformatics 22, no. 14 (July 15, 2006): e446-e453. http://dx.doi.org/10.1093/bioinformatics/btl235.

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Baeza-Yates, Ricardo, and Gonzalo Navarro. "Integrating contents and structure in text retrieval." ACM SIGMOD Record 25, no. 1 (March 1996): 67–79. http://dx.doi.org/10.1145/381854.381890.

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Luna, David. "Integrating Ad Information: A Text-Processing Perspective." Journal of Consumer Psychology 15, no. 1 (January 2005): 38–51. http://dx.doi.org/10.1207/s15327663jcp1501_7.

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Dowell, K. G., M. S. McAndrews-Hill, D. P. Hill, H. J. Drabkin, and J. A. Blake. "Integrating text mining into the MGI biocuration workflow." Database 2009 (November 20, 2009): bap019. http://dx.doi.org/10.1093/database/bap019.

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Vroling, Bas, David Thorne, Philip McDermott, Teresa K. Attwood, Gert Vriend, and Steve Pettifer. "Integrating GPCR-specific information with full text articles." BMC Bioinformatics 12, no. 1 (2011): 362. http://dx.doi.org/10.1186/1471-2105-12-362.

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Qiu-Feng Wang, Fei Yin, and Cheng-Lin Liu. "Handwritten Chinese Text Recognition by Integrating Multiple Contexts." IEEE Transactions on Pattern Analysis and Machine Intelligence 34, no. 8 (August 2012): 1469–81. http://dx.doi.org/10.1109/tpami.2011.264.

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Дисертації з теми "INTEGRATING TEXT"

1

Keith, Karin J., and Renee Rice Moran. "Integrating Text Sets and Common Core." Digital Commons @ East Tennessee State University, 2013. https://dc.etsu.edu/etsu-works/3612.

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Shmueli, Yael. "Integrating speech and visual text in multimodal interfaces." Thesis, University College London (University of London), 2005. http://discovery.ucl.ac.uk/1446688/.

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Анотація:
This work systematically investigates when and how combining speech output and visual text may facilitate processing and comprehension of sentences. It is proposed that a redundant multimodal presentation of speech and text has the potential for improving sentence processing but also for severely disrupting it. The effectiveness of the presentation is assumed to depend on the linguistic complexity of the sentence, the memory demands incurred by the selected multimodal configuration and the characteristics of the user. The thesis employs both theoretical and empirical methods to examine this claim. At the theoretical front, the research makes explicit features of multimodal sentence presentation and of structures and processes involved in multimodal language processing. Two entities are presented: a multimodal design space (MMDS) and a multimodal user model (MMUM). The dimensions of the MMDS include aspects of (i) the sentence (linguistic complexity, c.f., Gibson, 1991), (ii) the presentation (configurations of media), and (iii) user cost (a function of the first two dimensions). The second entity, the MMUM, is a cognitive model of the user. The MMUM attempts to characterise the cognitive structures and processes underlying multimodal language processing, including the supervisory attentional mechanisms that coordinate the processing of language in parallel modalities. The model includes an account of individual differences in verbal working memory (WM) capacity (c.f. Just and Carpenter, 1992) and can predict the variation in the cognitive cost experienced by the user when presented with different contents in a variety of multimodal configurations. The work attempts to validate through 3 controlled studies with users the central propositions of the MMUM. The experimental findings indicate the validity of some features of the MMUM but also the need for further refinement. Overall, they suggest that a durable text may reduce the processing cost of demanding sentences delivered by speech, whereas adding speech to such sentences when presented visually increases processing cost. Speech can be added to various visual forms of text only if the linguistic complexity of the sentence imposes a low to moderate load on the user. These conclusions are translated to a set of guidelines for effective multimodal presentation of sentences. A final study then examines the validity of some of these guidelines in an applied setting. Results highlight the need for an enhanced experimental control. However, they also demonstrate that the approach used in this research can validate specific assumptions regarding the relationship between cognitive cost, sentence complexity and multimodal configuration aspects and thereby to inform the design process of effective multimodal user interfaces.
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Mastronardo, Claudio. "Integrating Deep Contextualized Word Embeddings into Text Summarization Systems." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18468/.

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Анотація:
In questa tesi saranno usate tecniche di deep learning per affrontare unodei problemi più difficili dell’elaborazione automatica del linguaggio naturale:la generazione automatica di riassunti. Dato un corpus di testo, l’obiettivoè quello di generare un riassunto che sia in grado di distillare e comprimerel’informazione dall’intero testo di partenza. Con i primi approcci si é provatoa catturare il significato del testo attraverso l’uso di regole scritte dagliumani. Dopo questa era simbolica basata su regole, gli approcchi statistici hanno preso il sopravvento. Negli ultimi anni il deep learning ha impattato positivamente ogni area dell’elaborazione automatica del linguaggionaturale, incluso la generazione automatica dei riassunti. In questo lavoroi modelli pointer-generator [See et al., 2017] sono utilizzati in combinazionea pre-trained deep contextualized word embeddings [Peters et al., 2018]. Sivaluta l’approccio sui due più grossi dataset per la generazione automaticadei riassunti disponibili ora: il dataset CNN/Daily Mail e il dataset Newsroom. Il dataset CNN/Daily Mail è stato generato partendo dal dataset diQuestion Answering pubblicato da DeepMind [Hermann et al., 2015], concatenando le frasi di highlight delle news e formando cosı̀ dei riassunti multifrase. Il dataset Newsroom [Grusky et al., 2018] è, invece, il primo datasetesplicitamente costruito per la generazione automatica di riassunti. Comprende un milione di coppie articolo-riassunto con diversi gradi di estrattività/astrattività a diversi ratio di compressione.L’approccio è valutato sui test-set con l’uso della metrica Recall-Oriented Understudy for Gisting Evaluation (ROUGE). Questo approccio causa un sostanzioso aumento nelle performance per il dataset Newsroom raggiungendo lo stato dell’arte sul valore di ROUGE-1 e valori competitivi per ROUGE-2 e ROUGE-L.
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Blunt, Aurelia LaShawn. "Teachers' Perceptions of Integrating Social Studies Text During Reading - Language Arts Instruction." ScholarWorks, 2015. http://scholarworks.waldenu.edu/dissertations/1377.

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Анотація:
In a large urban school system located in a metropolitan city in the southeastern United States, third- and fifth-grade minority students in Title I elementary schools are performing below proficiency in social studies on the statewide standardized assessments. The lack of exposure to the social studies curriculum continues to hinder minority students from successfully comprehending complex informational text, which is important to their success in the newly adopted Common Core State Standards (CCSS). The purpose of this qualitative study was to explore the problem teachers faced with an insufficient amount of time for teaching social studies content and the recent requirement to increase student exposure to informational text. The research used Lev Vygotsky's theory of social constructivism to provide a framework for the methods used in this paper. To address these problems, this study explored two third-grade and two fifth-grade language arts teachers' perceptions of integrating social studies text during their reading-language arts block. Further, the study observed teachers as they integrated social studies text to teach reading. Data for this case study were compiled from interviews, observations, and focus group discussions. The data were reviewed and coded to identify major themes and were then analyzed to generalize data findings. Teachers reported integrating social studies text afforded them the opportunity to maximize instructional time, teach the CCSS, and expose students to more informational text. Implications for positive social change include enabling teachers to identify the benefits of integrating social studies text during reading-language arts instruction and enabling minority students to increase their scores on the statewide social studies assessment.
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Gerner, Lars Martin Anders. "Integrating text-mining approaches to identify entities and extract events from the biomedical literature." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/integrating-textmining-approaches-to-identify-entities-and-extract-events-from-the-biomedical-literature(44f8e79a-3782-4687-85c7-eee1fda5cb76).html.

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Анотація:
The amount of biomedical literature available is increasing at an exponential rate and is becoming increasingly difficult to navigate. Text-mining methods can potentially mitigate this problem, through the systematic and large-scale extraction of structured information from inherently unstructured biomedical text. This thesis reports the development of four text-mining systems that, by building on each other, has enabled the extraction of information about a large number of published statements in the biomedical literature. The first system, LINNAEUS, enables highly accurate detection ('recognition') and identification ('normalization') of species names in biomedical articles. Building on LINNAEUS, we implemented a range of improvements in the GNAT system, enabling high-throughput gene/protein detection and identification. Using gene/protein identification from GNAT, we developed the Gene Expression Text Miner (GETM), which extracts information about gene expression statements. Finally, building on GETM as a pilot project, we constructed the BioContext integrated event extraction system, which was used to extract information about over 11 million distinct biomolecular processes in 10.9 million abstracts and 230,000 full-text articles. The ability to detect negated statements in the BioContext system enables the preliminary analysis of potential contradictions in the biomedical literature. All tools (LINNAEUS, GNAT, GETM, and BioContext) are available under open-source software licenses, and LINNAEUS and GNAT are available as online web-services. All extracted data (36 million BioContext statements, 720,000 GETM statements, 72,000 contradictions, 37 million mentions of species names, 80 million mentions of gene names, and 57 million mentions of anatomical location names) is available for bulk download. In addition, the data extracted by GETM and BioContext is also available to biologists through easy-to-use search interfaces.
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6

Xu, Zhe. "A Sentiment Analysis Model Integrating Multiple Algorithms and Diverse Features." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1275400109.

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Albqmi, Aisha Rashed M. "Integrating three-way decisions framework with multiple support vector machines for text classification." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/235898/7/Aisha_Rashed_Albqmi_Thesis_.pdf.

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Identifying the boundary between relevant and irrelevant objects in text classification is a significant challenge due to the numerous uncertainties in text documents. Most existing binary text classifiers cannot deal effectively with this problem due to the issue of over-fitting. This thesis proposes a three-way decision model for dealing with the uncertain boundary to improve the binary text classification performance by integrating the distinct aspects of three-way decisions theory and the capacities of the Support Vector Machine. The experimental results show that the proposed models outperform baseline models on the RCV1, Reuters-21578, and R65CO datasets.
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8

Calli, Cagatay. "Improving Search Result Clustering By Integrating Semantic Information From Wikipedia." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612554/index.pdf.

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Анотація:
Suffix Tree Clustering (STC) is a search result clustering (SRC) algorithm focused on generating overlapping clusters with meaningful labels in linear time. It showed the feasibility of SRC but in time, subsequent studies introduced description-first algorithms that generate better labels and achieve higher precision. Still, STC remained as the fastest SRC algorithm and there appeared studies concerned with different problems of STC. In this thesis, semantic relations between cluster labels and documents are exploited to filter out noisy labels and improve merging phase of STC. Wikipedia is used to identify these relations and methods for integrating semantic information to STC are suggested. Semantic features are shown to be effective for SRC task when used together with term frequency vectors. Furthermore, there were no SRC studies on Turkish up to now. In this thesis, a dataset for Turkish is introduced and a number of methods are tested on Turkish.
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9

Leroy, Gondy A. "Facilitating knowledge discovery by integrating bottom-up and top-down knowledge sources: A text mining approach." Diss., The University of Arizona, 2003. http://hdl.handle.net/10150/280294.

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This dissertation aims to discover synergistic combinations of top-down (ontologies), interactive (relevance feedback), and bottom-up (machine learning) knowledge encoding techniques for text mining. The strength of machine learning techniques lies in their coverage and efficiency because they can discover new knowledge without human intervention. The output, however, is often imprecise and irrelevant. Human knowledge, top-down or interactively encoded, may remedy this. The research question addressed is if knowledge discovery can become more precise and relevant with hybrid systems. Three different combinations are evaluated. The first study investigates an ontology, the Unified Medical Language System (UMLS), combined with an automatically created thesaurus to dynamically adjust the thesaurus' output. The augmented thesaurus was added to a medical, meta-search portal as a keyword suggester and compared with the unmodified thesaurus and UMLS. Users preferred the hybrid approach. Thus, the combination of the ontology with the thesaurus was better than the components separately. The second study investigates implicit relevance feedback combined with genetic algorithms designed to adjust user queries for online searching. These were compared with pure relevance feedback algorithms. Users were divided into groups based on their overall performance. The genetic algorithm significantly helped low achievers, but hindered high achievers. Thus, the interactively elicited knowledge from relevance feedback was judged insufficient to guide machine learning for all users. The final study investigates ontologies combined with two natural language processing techniques: a shallow parser and an automatically created thesaurus. Both capture relations between phrases in biomedical text. Qualified researchers found all terms to be precise; however, terms that belonged to ontologies were more relevant. Parser relations were all precise. Thesaurus relations were less precise, but precision improved for relations that had their terms represented in ontologies. Thus, this integration of ontologies with natural language processing provided good results. In general, it was concluded that top-down encoded knowledge could be effectively integrated with bottom-up encoded knowledge for knowledge discovery in text. This is particularly relevant to business fields, which are text and knowledge intensive. In the future, it will be worthwhile to extend the parser and also to test similar hybrid approaches for data mining.
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10

Mason, Amanda. "Integrating a focus on form into task-based language teaching : an investigation of four communicative tasks conducted by advanced learners of English using synchronous text-based computer-mediated communications." Thesis, Liverpool John Moores University, 2010. http://researchonline.ljmu.ac.uk/6010/.

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Книги з теми "INTEGRATING TEXT"

1

Technical and professional communicaton: Integrating text and visuals. Newburyport, MA: Focus Pub./R. Pullins Co., 2009.

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2

C, Moreland Milton, ed. Between text and artifact: Integrating archaeology in biblical studies teaching. Leiden: Brill, 2004.

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3

(Conference), Text Retrieval '85. Integrating text with non-text: A picture is worth 1k words : proceedings of the Institute of Information Scientists Text Retrieval '85 Conference. London: Taylor Graham, 1986.

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1949-, Kimberley Robert, Institute of Information Scientists. Southern Branch., and Institute of Information Scientists, eds. Integrating text with non-text: A picture is worth 1k words : proceedings of the Institute of Information Scientists Text Retrieval '85 conference. London: Taylor Graham, 1986.

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5

Pre-exilic Israel, the Hebrew Bible, and archaeology: Integrating text and artefact. New York: T&T Clark International, 2011.

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6

McLean, Gerald. More like this: Development of digital file management methodologies (including linking to text data) for integrating text and images. London: LCP, 2003.

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7

Paul, Hoffman. Macintosh paperwork: Integrating Microsoft® products. Berkeley, Calif: Osborne McGraw-Hill, 1986.

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8

Smith, N. Craig. Mainstreaming corporate responsibility: Cases and text for integrating corporate responsibility across the business school curriculum. Hoboken, NJ: Wiley, 2009.

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9

O, Herzog, Rollinger Claus-Rainer, and IBM Deutschland, eds. Text understanding in LILOG: Integrating computational linguistics and artificial intelligence : final report on the IBM Germany LILOG-project. Berlin: Springer-Verlag, 1991.

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10

Mind, body, and medicine: An integrative text. Oxford: Oxford University Press, 2001.

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Частини книг з теми "INTEGRATING TEXT"

1

Pascual, Elsa. "Integrating text formatting and text generation." In Trends in Natural Language Generation An Artificial Intelligence Perspective, 205–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-60800-1_31.

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Wainer, Howard. "Integrating Figures and Text." In Visual Revelations, 143–45. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-2282-8_18.

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Grossman, David A., and Ophir Frieder. "Integrating Structured Data and Text." In The Kluwer International Series in Engineering and Computer Science, 153–84. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5539-1_5.

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Grossman, David A., and Ophir Frieder. "Integrating Structured Data and Text." In Information Retrieval, 211–55. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-1-4020-3005-5_6.

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Kopeček, Ivan, Radek Ošlejšek, and Jaromír Plhák. "Integrating Dialogue Systems with Images." In Text, Speech and Dialogue, 632–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32790-2_77.

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Barnard, Kobus. "Text and Speech Processing." In Computational Methods for Integrating Vision and Language, 55–61. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-031-01814-5_5.

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Stafura, Joseph Z., and Charles A. Perfetti. "Integrating word processing with text comprehension." In Studies in Written Language and Literacy, 9–32. Amsterdam: John Benjamins Publishing Company, 2017. http://dx.doi.org/10.1075/swll.15.02sta.

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Kwon, Namhee, and Eduard Hovy. "Integrating Semantic Frames from Multiple Sources." In Computational Linguistics and Intelligent Text Processing, 1–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11671299_1.

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Quemy, Alexandre, and Robert Wrembel. "On Integrating and Classifying Legal Text Documents." In Lecture Notes in Computer Science, 385–99. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59003-1_25.

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Wiedemann, Gregor. "Integrating Text Mining Applications for Complex Analysis." In Text Mining for Qualitative Data Analysis in the Social Sciences, 55–166. Wiesbaden: Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-15309-0_3.

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Тези доповідей конференцій з теми "INTEGRATING TEXT"

1

Ai, Lisi, Baoli Gao, Jianbing Zheng, and Ming Gao. "On Improving Text Generation Via Integrating Text Coherence." In 2019 IEEE 6th International Conference on Cloud Computing and Intelligence Systems (CCIS). IEEE, 2019. http://dx.doi.org/10.1109/ccis48116.2019.9073682.

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Mei, Jie, Xiang Jiang, Aminul Islam, Abidalrahman Moh'd, and Evangelos Milios. "Integrating Global Attention for Pairwise Text Comparison." In DocEng '18: ACM Symposium on Document Engineering 2018. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3209280.3229119.

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Jiang, Suqi, Jason Lewris, Michael Voltmer, and Hongning Wang. "Integrating rich document representations for text classification." In 2016 Systems and Information Engineering Design Symposium (SIEDS). IEEE, 2016. http://dx.doi.org/10.1109/sieds.2016.7489319.

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Jankowski, Jacek, Krystian Samp, Izabela Irzynska, Marek Jozwowicz, and Stefan Decker. "Integrating text with video and 3D graphics." In the 28th international conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1753326.1753524.

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Harvey, Terrence, and Sandra Carberry. "Integrating text plans for conciseness and coherence." In the 36th annual meeting. Morristown, NJ, USA: Association for Computational Linguistics, 1998. http://dx.doi.org/10.3115/980845.980931.

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Harvey, Terrence, and Sandra Carberry. "Integrating text plans for conciseness and coherence." In the 17th international conference. Morristown, NJ, USA: Association for Computational Linguistics, 1998. http://dx.doi.org/10.3115/980451.980931.

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Li, Yujia. "The visual beauty of text overlay images of different proportions of pictures." In Intelligent Human Systems Integration (IHSI 2023) Integrating People and Intelligent Systems. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1002881.

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Perceived visual aesthetics is of great significance for the design of human-computer interaction interface. There is much research on interface aesthetics in the academic community. There is evidence that perceived visual aesthetics has an important impact on user experience and interaction, and many scholars have put forward the calculation model of perceived visual aesthetics. This study research the text overlay image. Compared with the traditional text surround image, the text overlay image changes the visual perception aesthetics of the image by embedding the text into the image. Text overlay image is usually superimposed on the image by a piece of text or several pieces of text, which blocks the background area of the image and affects the overall interface aesthetics. However, the text overlay image is applied to various places. In this study, the background white space calculation model (WBB) based on bounding box is used to calculate the perceived visual aesthetics. Explore the visual aesthetics of text overlay images under three proportions: golden section ratio (1:0.618), root mean square ratio (1:0.707) and integer ratio (1:1). The experiment uses the calculation model to obtain the proportion of the blank area of the text covered image in the image background. The subjects' subjective evaluation of different proportion interfaces is obtained through the Likert scale. The results of the two are compared to obtain the proportion of the optimal visual beauty under the text covered image. The results show that: ① in terms of the image length width ratio, the visual aesthetics of the text overlay image with the length width ratio of 1:0.618 is better when the text line spacing is 1 times, and the visual aesthetics of the image with the length width ratio of 1:0.707 is better when the text line spacing is 1.5 times. When the line spacing is 1 and 1.5 times, the visual aesthetics of the image with length width ratio of 1:1 is the worst; ② In terms of line spacing, when the line spacing is the same (1 or 1.5 times the line spacing), the subjects think that the proportion of the blank area of the text covered image with high visual aesthetics in the image background is 0.7218-0.9040. When the line spacing is different (1 and 1.5 times the line spacing), it can be speculated that the visual aesthetics of the text covered image is closely related to the blank area of the image background, In order to obtain a text overlay image with high visual aesthetics, we should consider not only the proportion of the image, but also the blank area of the image background.
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Wang, Qiu-Feng, Fei Yin, and Cheng-Lin Liu. "Integrating Language Model in Handwritten Chinese Text Recognition." In 2009 10th International Conference on Document Analysis and Recognition. IEEE, 2009. http://dx.doi.org/10.1109/icdar.2009.96.

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Jiang, Wei, and Zhong Jin. "Integrating Bidirectional LSTM with Inception for Text Classification." In 2017 4th IAPR Asian Conference on Pattern Recognition (ACPR). IEEE, 2017. http://dx.doi.org/10.1109/acpr.2017.113.

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Fragoudis, Dimitris, Dimitris Meretakis, and Spiros Likothanassis. "Integrating feature and instance selection for text classification." In the eighth ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/775047.775120.

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Звіти організацій з теми "INTEGRATING TEXT"

1

Prior, Lorraine, Carl Fossa, David Ward, Jun Sun, Patrick Boehm, Edward Kuczynski, John Cain, and Thomas Mak. Tactical Network Integration Test Framework. Fort Belvoir, VA: Defense Technical Information Center, May 2011. http://dx.doi.org/10.21236/ada570872.

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2

Sakell, Leonidas. Integrating Test & Evaluation into the SBA Process. Fort Belvoir, VA: Defense Technical Information Center, May 2001. http://dx.doi.org/10.21236/ada386254.

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3

Hillestad, Torgeir Martin. The Metapsychology of Evil: Main Theoretical Perspectives Causes, Consequences and Critique. University of Stavanger, 2014. http://dx.doi.org/10.31265/usps.224.

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The purpose of this text or dissertation is to throw some basic light on a fundamental problem concerning manhood, namely the question of evil, its main sources, dynamics and importance for human attitudes and behaviour. The perspective behind the analysis itself is that of psychology. Somebody, or many, may feel at bit nervous by the word “evil” itself. It may very well be seen as too connected to religion, myth and even superstition. Yet those who are motivated to lose oneself in the subject retain a deep interest in human destructiveness, malevolence and hate, significant themes pointing at threatening prospects for mankind. The text is organized or divided into four main ordinary chapters, the three first of them organized or divided into continuous and numbered sections. A crucial point or question is of cause how to define evil itself. It can of cause be done both intentional, instrumental and by consequence. Other theorists however have stated that the concept of evil exclusively rests on a myth originated in the Judean-Christian conception of Satan and ultimate evil. This last argument presupposes evil itself as non-existent in the real rational world. It seems however a fact that most people attach certain basic meaning to the concept, mainly that it represents ultimately bad and terrible actions and behaviour directed toward common people for the purpose of bringing upon them ultimate pain and suffer. However, there is no room for essentialism here, meaning that we simply can look “inside” some original matter to get to know what it “really” is. Rather, a phenomenon gets its identity from the constituted meaning operating within a certain human communities and contexts loaded with intentionality and inter-subjective meaning. As mentioned above, the concept of evil can be interpreted both instrumental and intentional, the first being the broadest of them. Here evil stands for behaviour and human deeds having terrifying or fatal consequences for subjects and people or in general, regardless of the intentions behind. The intentional interpretation however, links the concept to certain predispositions, characteristics and even strong motives in subjects, groups and sometimes political systems and nations. I will keep in mind and clear the way for both these perspectives for the discussion in prospect. This essay represents a psychological perspective on evil, but makes it clear that a more or less complete account of such a psychological view also should include a thorough understanding or integration of some basic social and even biological assumptions. However, I consider a social psychological position of significant importance, especially because in my opinion it represents some sort of coordination of knowledge and theoretical perspectives inherent in the subject or problem itself, the main task here being to integrate perspectives of a psychological as well as social and biological kind. Since humans are essential social creatures, the way itself to present knowledge concerning the human condition, must be social of some sort and kind, however not referring to some kind of reductionism where social models of explanation possess or holds monopoly. Social and social psychological perspectives itself represents parts of the whole matter regarding understanding and explanation of human evil. The fact that humans present, or has to represent themselves as humans among other humans, means that basically a social language is required both to explain and describe human manners and ways of being. This then truly represents its own way or, more correctly, level or standard of explanation, which makes social psychology some sort of significant, though not sufficient. More substantial, the vision itself of integrating different ontological and theoretical levels and objects of science for the purpose of manifesting or make real a full-fledged psychological perspective on evil, should be considered or characterized a meta-psychological perspective. The text is partially constructed as a review of existing theories and theorists concerning the matter of evil and logically associated themes such as violence, mass murder, genocide, antisocial behaviour in general, aggression, hate and cruelty. However, the demands of making a theoretical distinction between these themes, although connected, is stressed. Above all, an integral perspective combining different scientific disciplines is aimed at.
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ILLINOIS UNIV AT URBANA BECKMAN INST. Human Systems Integration. Test Operations Procedure. Fort Belvoir, VA: Defense Technical Information Center, October 2007. http://dx.doi.org/10.21236/ada480892.

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Norcross, Richard J. One degree micro-macro manipulator integration test. Gaithersburg, MD: National Institute of Standards and Technology, 2000. http://dx.doi.org/10.6028/nist.ir.6562.

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Connell, S., J. Ernsting, D. Kukan, and A. Currie. GEOSIS project-integration of text and spatial data for geoscience applications. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1990. http://dx.doi.org/10.4095/128099.

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Spurling, D. G. TMACS Test Procedure TP010: Integration summary. Revision 5. Office of Scientific and Technical Information (OSTI), August 1994. http://dx.doi.org/10.2172/10189114.

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Spurling, D. G. TMACS test procedure TP010: Integration summary. Revision 6. Office of Scientific and Technical Information (OSTI), September 1994. http://dx.doi.org/10.2172/10185170.

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Hunt, W., T. Avi, B. Hatch, and J. Krueger. nEXO Team Active Georgetown University: Systems Integration and Test. Office of Scientific and Technical Information (OSTI), June 2021. http://dx.doi.org/10.2172/1797560.

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Ryan, T. G. The integration of Human Factors (HF) in the SAR process training course text. Office of Scientific and Technical Information (OSTI), March 1995. http://dx.doi.org/10.2172/130627.

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